Abstract
EEG remains useful and irreplaceable in multiple clinical applications and scientific researches, with regard to its massive advantages. As EEG continues to spread widely over time, EEG signal processing is still a highly promising and evolving field. Recent developments of EEG processing techniques, such as advanced machine learning for EEG and EEG-related multimodality brain imaging, are expected to make EEG a more powerful and versatile tool in the future.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Biasiucci A, Franceschiello B, Murray MM. Electroencephalography. Curr Biol. 2019;29(3):R80–5.
Cavanagh JF. Electrophysiology as a theoretical and methodological hub for the neural sciences. Psychophysiology. 2019;56(2):e13314. https://doi.org/10.1111/psyp.13314.
Sejnowski TJ, Churchland PS, Movshon JA. Putting big data to good use in neuroscience. Nat Neurosci. 2014;17(11):1440–1.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Zhang, Z., Hu, L. (2019). Summary and Conclusions. In: Hu, L., Zhang, Z. (eds) EEG Signal Processing and Feature Extraction. Springer, Singapore. https://doi.org/10.1007/978-981-13-9113-2_20
Download citation
DOI: https://doi.org/10.1007/978-981-13-9113-2_20
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9112-5
Online ISBN: 978-981-13-9113-2
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)